code: def rgb_to_xyz(image: torch.Tensor) -> torch.Tensor:
      r"""Convert a RGB image to XYZ.
  
      .. image:: _static/img/rgb_to_xyz.png
  
      Args:
          image: RGB Image to be converted to XYZ with shape :math:`(*, 3, H, W)`.
  
      Returns:
           XYZ version of the image with shape :math:`(*, 3, H, W)`.
  
      Example:
          >>> input = torch.rand(2, 3, 4, 5)
          >>> output = rgb_to_xyz(input)  # 2x3x4x5
      """
      if not isinstance(image, torch.Tensor):
          raise TypeError(
              f"Input type is not a torch.Tensor. Got {type(image)}"
          )
  
      if len(image.shape) < 3 or image.shape[-3] != 3:
          raise ValueError(
              f"Input size must have a shape of (*, 3, H, W). Got {image.shape}"
          )
  
      r: torch.Tensor = image[..., 0, :, :]
      g: torch.Tensor = image[..., 1, :, :]
      b: torch.Tensor = image[..., 2, :, :]
  
      x: torch.Tensor = 0.412453 * r + 0.357580 * g + 0.180423 * b
      y: torch.Tensor = 0.212671 * r + 0.715160 * g + 0.072169 * b
      z: torch.Tensor = 0.019334 * r + 0.119193 * g + 0.950227 * b
  
      out: torch.Tensor = torch.stack([x, y, z], -3)
  
      return out
  
file_path: kornia/kornia/color/xyz.py
imports: import torch
  from torch import nn
label_desc: Use image node_id 1 for calling a global function with example usage: rgb_to_xyz(image) and returns: out